The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way.” In this article I respond to this critique and illustrate the critical methodological role that robustness plays as an aim of scientific inquiry.

The following analysis shows how developments in epistemic logic can play a nontrivial role in cognitive neuroscience. We argue that the striking correspondence between two modes of identification, as distinguished in the epistemic context, and two cognitive systems distinguished by neuroscientific investigation of the visual system (the “where” and “what” systems) is not coincidental, and that it can play a clarificatory role at the most fundamental levels of neuroscientific theory.

Recently philosophers of biology have argued over whether or not Newtonian mechanics provides a useful analogy for thinking about evolutionary theory. For philosophers, the canonical presentation of this analogy is Sober's. Matthen and Ariew and Walsh, Lewins, and Ariew argue that this analogy is deeply wrong-headed. Here I argue that the analogy is indeed useful, however, not in the way it is usually interpreted. The Newtonian analogy depends on having the proper analogue of Newton's First Law. That analogue is what McShea and Brandon call the Zero Force Evolutionary Law (ZFEL). According to the ZFEL, change, not stasis, is the default state of evolutionary systems.

It is argued herein that there are two distinct ways in which all observation vocabularies are prejudiced with respect to theory. An argument based on the demands of adequate translation is invoked to show that even the simplest of our observation predicates must display the first and more obvious grade of bias—intensional bias. It is also argued that any observation vocabulary whose predicates are corrigibly applicable must manifest a second and equally serious grade of bias—extensional bias—independently of whatever intensional bias its predicates may or may not have.

Current discussions of science—both popular and philosophical—often represent the development of science in our civilization as a gradual process of purification from superstitious, religious, and metaphysical elements. This purification is usually presumed to be complete by now—although there may be occasional lapses on the part of individual scientists. That science has changed in character over the centuries is a truism; that it has increasingly loosened ancient ties with magic, religion, and speculative philosophy is an easily substantiated historical thesis. This much admitted, however, an interesting question remains over for discussion: is science by its very nature independent of philosophy? This question has only as much meaning as its two key words (“science” and “philosophy”). According to one common view, “science” would signify some cumulative heritage of methods, principles, and results, while “philosophy” would signify a certain tradition of writings in which the later constantly refer to the earlier, but which otherwise exhibit no discernible uniformity of methods, principles, or results. On this view, then, science is essentially monistic while philosophy is essentially pluralistic.

Science progresses if we succeed in rendering the objects of scientific inquiry more comprehensively or more precisely. Popper tries to formalize this venerable idea. According to him the most comprehensive and most precise description of the world is given by the set T of all true statements. A hypothesis comes the closer to T, or has the more verisimilitude, the more true consequences and the fewer false consequences it implies. Popper proposes to order hypotheses by the inclusion relations between the sets of their true and of their false consequences (“truth contents” and “falsity contents”). A partial ordering would permit one to decide whether the substitution of theory t1 by t2 represents scientific progress. But because of the logical relations between the elements of the sets of logical consequences, or contents, false hypotheses cannot be compared. As our theories usually turn out to be false sooner or later, they can seldom be compared as to their verisimilitude and when they can, the result depends only on which theory implies the other and on their truth-values. Popper even tries to define a measure of verisimilitude on the partial ordering. It has to fail for the same reason. In addition he tries to relativize the concept of a content and fails. What is more, any attempt at defining a measure of better or worse correspondence to the whole truth must fail, as there is no justification for saying that any true primitive sentence asserts as much about reality as some other primitive sentence, or more.

In this paper, I develop a naturalistic conception of evolutionary progress. I argue that the Waddingtonian notion of adaptability can be embedded meaningfully into a framework which views living things as nonequilibrium structures. This thermodynamic interpretation places great emphasis on the dynamics of environmental change, whereas the classical conceptions are based on equilibrium conceptions of the evolutionary process. What improves in evolution is the ability of living things to stay alive in increasingly heterogeneous environments.

The relations between simplicity and economy, and between simplicity and complexity, are briefly discussed, and it is suggested that an appearance of simplicity may arise out of the matching of two complexities, e.g. in the perception of a simple color. Following out this idea, it is shown that scientific activity may be regarded as a matching of theoretical complexity against the complexity of nature, which leads to an expectation of an optimum theoretical complexity for successful scientific work. Some senses of “success” in this context are discussed, and the role of computing machines in helping to achieve it assessed.

Additional results are reported on the author's earlier generalization of Richard Jeffrey's solution to the problem of old evidence and new explanation.

Election prediction by means of opinion polling is a rare empirical success story for social science. I examine the details of a prominent case, drawing two lessons of more general interest: (1) Methodology over metaphysics. Traditional metaphysical criteria were not a useful guide to whether successful prediction would be possible; instead, the crucial thing was selecting an effective methodology. (2) Which methodology? Success required sophisticated use of case-specific evidence from opinion polling. The pursuit of explanations via general theory or causal mechanisms, by contrast, turned out to be precisely the wrong path—contrary to much recent philosophy of social science.

In discussion of mechanisms, philosophers often debate about whether quantitative descriptions of generalizations or qualitative descriptions of operations are explanatorily fundamental. I argue that these debates have erred by conflating the explanatory roles of generalizations and patterns. Patterns are types of variations within or between quantities in a mechanism over time or across conditions. While these patterns must often be represented in addition to descriptions of operations in order to explain a phenomenon, they are not equivalent to generalizations because their explanatory role does not depend on any specific facts about their scope or domain of invariance.

Recently, Estes and Arnold claimed to have “solved” the paradox of evolutionary stasis; they claim that stabilizing selection, and only stabilizing selection, can explain the patterns of evolutionary divergence observed over “all timescales.” While Estes and Arnold clearly think that they have identified the processes that produce evolutionary stasis, they have not. Instead, Estes and Arnold identify a particular evolutionary pattern but not the processes that produce that pattern. This mistake is important; the slippage between pattern and process is common in population and quantitative genetics and contributes to a persistent misunderstanding of the nature of explanations in evolutionary biology.

The current antireductionist consensus rests in part on the indefensibility of the deductive-nomological model of explanation, on which classical reductionism depends. I argue that the DN model is inessential to the reductionist program and that mechanism provides a better framework for thinking about reductionism. This runs counter to the contemporary mechanists’ claim that mechanism is an alternative to reductionism. I demonstrate that mechanists are committed to reductionism, as evidenced by the historical roots of the contemporary mechanist program. This view shares certain core commitments with reductionism. It is these shared commitments that constitute the essential elements of the reductionist program.

Various fault modes of determinism in classical physics are outlined. It is shown how quantum mechanics can cure some forms of classical indeterminism.

I argue that information about the distal causes of moral beliefs, such as evolution, is only relevant for assessing the epistemic status of moral beliefs in cases where we cannot determine whether the proximal processes producing these beliefs are reliable just by examining the properties of these proximal processes. Any investigation into the epistemic status of moral beliefs given their causes should start with a look at proximal causes—not at evolution. I discuss two proximal psychological influences on moral beliefs—disgust and sympathy—to demonstrate the feasibility of drawing epistemic conclusions from an examination of proximal causes alone.

Kitcher has proposed an ideal-theory account—well-ordered science (WOS)—of the collective good that science’s research agenda should promote. Against criticism regarding WOS’s action guidance, Kitcher has advised critics not to confuse substantive ideals and the ways to arrive at them, and he has defended WOS as a necessary and useful ideal for science policy. I provide a distinction between two types of ideal theories that helps clarifying WOS’s elusive nature. I use this distinction to argue that the action-guidance problem that WOS faces remains even under the aims/means distinction because the WOS’s failure is more basic than critics have suggested.

This article is about a start-up problem in scientific practice. Specifically, it is about the problem of justifying paleontological correlation—the practice of using fossils to establish time relations among fossiliferous rocks. Paleontological correlation was the key to assembling a geological timescale during the nineteenth century and remains an important practice in stratigraphic geology to this day. Yet contrary to philosophical expectations, this practice lacked a robust theoretical justification during the first half of the nineteenth century. This article examines what this lack of justification amounted to, as well as how the method of paleontological correlation was justified in practice.

The universality of critical phenomena is best explained by appeal to the Renormalization Group (RG). Batterman and Morrison, among others, have claimed that this explanation is irreducible. I argue that the RG account is reducible but that the higher-level explanation ought not to be eliminated. I demonstrate that the key assumption on which the explanation relies—the scale invariance of critical systems—can be explained in lower-level terms. However, we should not replace the RG explanation with a bottom-up account; rather, we should acknowledge that the explanation appeals to dependencies that may be traced down to lower levels.

Faced with the paradox of undermining futures, Humeans have resigned themselves to accounts of chance that severely conflict with our intuitions. However, such resignation is premature: The problem is Humean Supervenience (HS), not Humeanism. This paper develops a projectivist Humeanism on which chance claims are understood as normative, rather than fact stating. Rationality constraints on the cotenability of norms and factual claims ground a factual-normative worlds semantics that, in addition to solving the Frege-Geach problem, delivers the intuitive set of possibilia for each chance law. Hence, the account does not entail HS, and the paradox does not arise. A confirmation theory is developed, and the Principal Principle is justified.

In this article, I offer a partial analysis of the role of values in qualitative data collection in social research. The partial analysis shows that nonepistemic values have both required and permissible roles to play during this phase of research. By appeal to the analysis, I reject the ideal of value-free science as applied to qualitative data collection, and I demonstrate why two alternative ideals should likewise be dismissed as standards for values in qualitative data collection. Also, I briefly discuss the extent to which the partial analysis carries over to quantitative data collection in social research.